New module for the adaptive level controlling functionality in the audio processing module

webrtc/modules/audio_processing/level_controller/signal_classifier.cc

Index: webrtc/modules/audio_processing/level_controller/signal_classifier.cc
diff --git a/webrtc/modules/audio_processing/level_controller/signal_classifier.cc b/webrtc/modules/audio_processing/level_controller/signal_classifier.cc
new file mode 100644
index 0000000000000000000000000000000000000000..b338ad3ff2378f0a8eaea1a4d5fa5622eff915fe
--- /dev/null
+++ b/webrtc/modules/audio_processing/level_controller/signal_classifier.cc
@@ -0,0 +1,173 @@
+/*
+ *  Copyright (c) 2016 The WebRTC project authors. All Rights Reserved.
+ *
+ *  Use of this source code is governed by a BSD-style license
+ *  that can be found in the LICENSE file in the root of the source
+ *  tree. An additional intellectual property rights grant can be found
+ *  in the file PATENTS.  All contributing project authors may
+ *  be found in the AUTHORS file in the root of the source tree.
+ */
+
+#include "webrtc/modules/audio_processing/level_controller/signal_classifier.h"
+
+#include <algorithm>
+#include <numeric>
+#include <vector>
+
+#include "webrtc/base/array_view.h"
+#include "webrtc/base/constructormagic.h"
+#include "webrtc/modules/audio_processing/aec/aec_rdft.h"
+#include "webrtc/modules/audio_processing/audio_buffer.h"
+#include "webrtc/modules/audio_processing/level_controller/down_sampler.h"
+#include "webrtc/modules/audio_processing/level_controller/noise_spectrum_estimator.h"
+#include "webrtc/modules/audio_processing/logging/apm_data_dumper.h"
+
+namespace webrtc {
+namespace {
+
+void RemoveDcLevel(rtc::ArrayView<float> x) {
+  RTC_DCHECK_LT(0u, x.size());
+  float mean = std::accumulate(x.data(), x.data() + x.size(), 0.f);
+  mean /= x.size();
+
+  for (float& v : x) {
+    v -= mean;
+  }
+}
+
+void PowerSpectrum(rtc::ArrayView<const float> x,
+                   rtc::ArrayView<float> spectrum) {
+  RTC_DCHECK_EQ(65u, spectrum.size());
+  RTC_DCHECK_EQ(128u, x.size());
+  float X[128];
+  std::copy(x.data(), x.data() + x.size(), X);
+  aec_rdft_forward_128(X);
+
+  float* X_p = X;
+  RTC_DCHECK_EQ(X_p, &X[0]);
+  spectrum[0] = (*X_p) * (*X_p);
+  ++X_p;
+  RTC_DCHECK_EQ(X_p, &X[1]);
+  spectrum[64] = (*X_p) * (*X_p);
+  for (int k = 1; k < 64; ++k) {
+    ++X_p;
+    RTC_DCHECK_EQ(X_p, &X[2 * k]);
+    spectrum[k] = (*X_p) * (*X_p);
+    ++X_p;
+    RTC_DCHECK_EQ(X_p, &X[2 * k + 1]);
+    spectrum[k] += (*X_p) * (*X_p);
+  }
+}
+
+webrtc::SignalClassifier::SignalType ClassifySignal(
+    rtc::ArrayView<const float> signal_spectrum,
+    rtc::ArrayView<const float> noise_spectrum,
+    ApmDataDumper* data_dumper) {
+  int num_stationary_bands = 0;
+  int num_highly_nonstationary_bands = 0;
+
+  // Detect stationary and highly nonstationary bands.
+  for (size_t k = 1; k < 40; k++) {
+    if (signal_spectrum[k] < 3 * noise_spectrum[k] &&
+        signal_spectrum[k] * 3 > noise_spectrum[k]) {
+      ++num_stationary_bands;
+    } else if (signal_spectrum[k] > 9 * noise_spectrum[k]) {
+      ++num_highly_nonstationary_bands;
+    }
+  }
+
+  data_dumper->DumpRaw("lc_num_stationary_bands", 1, &num_stationary_bands);
+  data_dumper->DumpRaw("lc_num_highly_nonstationary_bands", 1,
+                       &num_highly_nonstationary_bands);
+
+  // Use the detected number of bands to classify the overall signal
+  // stationarity.
+  if (num_stationary_bands > 15) {
+    return SignalClassifier::SignalType::kStationary;
+  } else if (num_highly_nonstationary_bands > 15) {
+    return SignalClassifier::SignalType::kHighlyNonStationary;
+  } else {
+    return SignalClassifier::SignalType::kNonStationary;
+  }
+}
+
+}  // namespace
+
+class FrameExtender {
+ public:
+  FrameExtender(size_t frame_size, size_t extended_frame_size)
+      : x_old_(extended_frame_size - frame_size, 0.f) {}
+
+  void ExtendFrame(rtc::ArrayView<const float> x,
+                   rtc::ArrayView<float> x_extended) {
+    RTC_DCHECK_EQ(x_old_.size() + x.size(), x_extended.size());
+    std::copy(x_old_.data(), x_old_.data() + x_old_.size(), x_extended.data());
+    std::copy(x.data(), x.data() + x.size(), x_extended.data() + x_old_.size());
+    std::copy(x_extended.data() + x_extended.size() - x_old_.size(),
+              x_extended.data() + x_extended.size(), x_old_.data());
+  }
+
+ private:
+  std::vector<float> x_old_;
+
+  RTC_DISALLOW_IMPLICIT_CONSTRUCTORS(FrameExtender);
+};
+
+SignalClassifier::SignalClassifier(ApmDataDumper* data_dumper)
+    : data_dumper_(data_dumper),
+      down_sampler_(data_dumper_),
+      noise_spectrum_estimator_(data_dumper_) {
+  Initialize(AudioProcessing::kSampleRate48kHz);
+}
+SignalClassifier::~SignalClassifier() {}
+
+void SignalClassifier::Initialize(int sample_rate_hz) {
+  aec_rdft_init();
+  down_sampler_.Initialize(sample_rate_hz);
+  frame_extender_.reset(new FrameExtender(80, 128));
+  sample_rate_hz_ = sample_rate_hz;
+  initialization_frames_left_ = 2;
+  consistent_classification_counter_ = 3;
+  last_signal_type_ = SignalClassifier::SignalType::kNonStationary;
+}
+
+void SignalClassifier::Analyze(const AudioBuffer& audio,
+                               SignalType* signal_type) {
+  // Compute the signal power spectrum.
+  float downsampled_frame[80];
+  down_sampler_.DownSample(rtc::ArrayView<const float>(
+                               audio.channels_const_f()[0], audio.num_frames()),
+                           downsampled_frame);
+  float extended_frame[128];
+  frame_extender_->ExtendFrame(downsampled_frame, extended_frame);
+  RemoveDcLevel(extended_frame);
+  float signal_spectrum[65];
+  PowerSpectrum(extended_frame, signal_spectrum);
+
+  // Classify the signal based on the estimate of the noise spectrum and the
+  // signal spectrum estimate.
+  *signal_type = ClassifySignal(signal_spectrum,
+                                noise_spectrum_estimator_.GetNoiseSpectrum(),
+                                data_dumper_);
+
+  // Update the noise spectrum based on the signal spectrum.
+  noise_spectrum_estimator_.Update(signal_spectrum,
+                                   initialization_frames_left_ > 0);
+
+  // Update the number of frames until a reliable signal spectrum is achieved.
+  initialization_frames_left_ = std::max(0, initialization_frames_left_ - 1);
+
+  if (last_signal_type_ == *signal_type) {
+    consistent_classification_counter_ =
+        std::max(0, consistent_classification_counter_ - 1);
+  } else {
+    last_signal_type_ = *signal_type;
+    consistent_classification_counter_ = 3;
+  }
+
+  if (consistent_classification_counter_ > 0) {
+    *signal_type = SignalClassifier::SignalType::kNonStationary;
+  }
+}
+
+}  // namespace webrtc